Cell-level Search Space. We follow NAS-Bench-201[1]}
to design our cell-level search space. It consists of 4,096 densely connected DAGs, which enables the evaluation of some weight-sharing NAS methods such as DARTS [2]} and ProxylessNAS [3]}.
As is shown in Figure REF , our cell-level search
space is obtained by assigning different operations (as edges) transforming
the feature map from the source node to the target node. The predefined
operation set has L=4 representative operations: zeroize, skip connection, 1x1 convolution, and 3x3 convolution. The convolution in our setting represents an operation sequence of ReLU, convolution, and batch normalization. Each DAG consists of 4 nodes and 6 edges, including basic residual block-like cell designs. The macro-level skeleton is fixed, which contains five modules with doubling channel and down-sampling feature map operations at the 1st, 3rd, 5th modules.
